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5th IEEE Conference on Energy Internet and Energy system Integration, EI2 2021

作者： Qi, Tengyun Xu, Fei Wu, Qiren Li, Yajing Liu, Jianping Li, He Wang, Yiming Li, Cuiping Li, Junhui China Three Gorges Corporation Beijing China Haidian District Beijing China Co. Ltd Beijing101100 China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China

ISBN: (纸本)9781665434256

High penetration wind power grid with energy storage system can effectively improve peak load regulation pressure and increase wind power capacity. In this paper, a capacity allocation method of energy storage system under peak load regulation scenario is proposed. The upper model combines the investment cost, operation cost, arbitrage income, environmental income, and wind power grid benefits during the entire life cycle of the energy storage system, with the goal of maximizing the net income during the energy storage life cycle;the lower model optimizes the charging and discharging power of the energy storage system according to each energy storage configuration scheme in the upper modeling, and its objective is to minimize the standard deviation of system net load and waste wind power. Finally, under the conditions of local grid load and wind power data, verified the effectiveness of capacity allocation strategy. © 2021 IEEE

关键词： Economic analysis

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Improved Comprehensive Inertial control for ESS Participating Primary Frequency Regulation Based on Fuzzy control 5

Improved Comprehensive Inertial Control for ESS Participatin...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Xiang, Yongjian Xu, Yunhui Zhou, Tao Dai, Zhongjian Ren, Bixing Zhang, Lei Nanjing University of Science and Technology School of Automation Nanjing China State Grid Lishui Power Supply Company Substation Operation Inspection Center Lishui China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Changzhou Power Supply Company Operation and Maintenance Department Changzhou China Jiangsu Electric Power Test Research Institute Co. Ltd. Nanjing China China Classification Society Product Plan Approval Center Nanjing China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

ESS (energy storage system) has many advantages such as flexible control, large throughput capacity and fast response speed and can provide strong support for system frequency stability with larger-scale renewable energy. In order to enhance the frequency regulation effect of ESS, this paper proposes an improved comprehensive inertia control strategy based on FC (fuzzy control). The conventional droop control is replaced by fuzzy control to improve the regulation performance and adaptivity of the whole process. SOC (state of charge) is adopted as the input of FC to consider the secure and stable constraints of ESS. In addition, FC is also applied to adjust the virtual inertia coefficients online. The proposed strategy combines the advantages of comprehensive inertial control and adaptive control and improve the frequency supporting ability of ESS under different operation conditions. Finally, simulations are conducted to demonstrate the feasibility of the proposed method. © 2022 IEEE.

关键词： Fuzzy control

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A Novel Design Method for the Large Space Wireless power Transfer system 1

A Novel Design Method for the Large Space Wireless Power Tra...

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1st IEEE International power Electronics and Application Symposium, PEAS 2021

作者： Yuan, Yaju Xia, Jinglin Min, Qinyun Xiao, Zhuangsheng Li, Siqi Kunming University of Science And Technology Dept. of Electrical Engineering Kunming China Jilin University State Key Laboratory of Automotive Simulation And Control Changchun China Electric Power Research Institute of Yunnan Power Grid Co Ltd Kunming China

ISBN: (纸本)9781665413596

The large space wireless power transfer (WPT) system that receiving energy from the spatial magnetic field is an attractive alternative for low and medium power mobile devices. The bio-electromagnetic safety is the main issue of the large space WPT system. To reduce the intensity of the space magnetic field while meeting the received power demand, a novel design method based on the magnetic field in space is proposed for the large space WPT system. Different with the traditional magnetic coupling design method, the proposed method takes the spatial magnetic field as the design object, and the primary side and secondary side are designed separately. The relationships between the transferred power and efficiency of the receiver under certain spatial magnetic field are analyzed. The maximum transmission power of the receivers is introduced. The primary side is designed to satisfy the safety requirement, and the receiving side is designed to provide the request power and efficiency. Providing a guideline for the parameter design of the receivers. To verify the effectiveness of the proposed method, a 5 W, 6.78 MHz prototype with a 2-m diameter and 0.5-m distance double-circular single-turn coil is designed. The maximum transmission power state is verified by simulation. The simulated results show that by using the proposed method, the receiving side can satisfy the power requirements while the spatial magnetic field decreased. © 2021 IEEE.

关键词： Magnetic fields

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Short-Term Wind power Forecasting Based on Two-Stage Feature Selection

Short-Term Wind Power Forecasting Based on Two-Stage Feature...

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Energy, Electrical and power Engineering (CEEPE), International Conference on

作者： Jie Zheng Zhewen Niu Xiaoqing Han Yuxiang Wu Xiaorui Cui Shanxi Key Laboratory of Power System Operation and Control Taiyuan University of Technology Taiyuan China Institute of Electricity Science Shanxi Province State Grid Electricity Company Taiyuan China

The forecasting of short-term wind power is influenced by complex and changeable factors, such as climate environment, and meteorological characteristics. A single input of model features is difficult to meet the accurate forecasting requirements. However, to consider all the influencing factors, the input feature redundancy will increase the computational complexity of the forecasting model and have a negative impact on the forecasting results. Therefore, accurate and efficient feature selection is the key to improving the accuracy of data-driven wind power forecasting. In this paper, a short-term wind power forecasting method based on two-stage feature selection is proposed. Firstly, the meteorological factors and environmental factors affecting wind power forecasting are screened by using the Pearson Correlation Coefficient method. Secondly, a feature selection method of attention mechanism considering temporal correlation is proposed, which dynamically mined the potential correlation between wind power output and input characteristics from the perspective of time, and independently extracted the information of historical key moments. Finally, a bidirectional gated cyclic neural network (BIGRU) is selected as the forecasting model, taking into account the influence of historical data and future information. The results show that the proposed PCC-TA-BIGRU short-term wind power forecasting model can accurately select the factors affecting wind power forecasting and effectively improve the accuracy of short-term wind power forecasting.

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Voltage Stability Evaluation Considering Successive Commutation Failure Risk

Voltage Stability Evaluation Considering Successive Commutat...

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control, Electronics and Computer Technology (ICCECT), IEEE International Conference on

作者： Rui Ding Hengtong Wang Zhaohao Jia Yuanzhen Zhu Changgang Li Yongji Cao State Grid Huangdao Power Supply Company State Grid Shandong Electric Power Company Qingdao China State Grid Zibo Power Supply Company State Grid Shandong Electric Power Company Zibo China State Grid Jinan Power Supply Company State Grid Shandong Electric Power Company Jinan China State Grid Shandong Electric Power Company State Grid Shandong Electric Power Research Institute Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Academy of Intelligent Innovation Shandong University Jinan China

In order to evaluate the risk of successive commutation failure caused by voltage drop, a deep learning-based method is proposed in this paper. First, the mechanism of successive commutation failures is analyzed and the minimum second voltage drop value of the commutation bus after short-circuit fault is utilized as the index to quantify the severity of line outage contingencies. Then, to quickly evaluate the impact of multi-line outage failures on DC systems, a deep learning-based assessment network is built, of which the output is the minimum second voltage drop value of the commutation bus and inputs are steady-state features related to network structure. Moreover, a bus impedance matrix formation approach based on Woodbury formula is proposed, which is used in the calculation of input features and search index. Finally, simulation results based on a real-life AC/DC power system demonstrate that the proposed method significantly improves the risk evaluation efficiency of successive commutation failure.

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Optimal control in Both Steady state and Transient Process with Unknown Disturbances

arXiv

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arXiv 2024年

作者： Li, Ming Wang, Zhaojian Liu, Feng Cao, Ming Yang, Bo The Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory of Power System The Department of Electrical Engineering Tsinghua University Beijing100084 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands

The scheme of online optimization as a feedback controller is widely used to steer the states of a physical system to the optimal solution of a predefined optimization problem. Such methods focus on regulating the physical states to the optimal solution in the steady state, without considering the performance during the transient process. In this paper, we simultaneously consider the performance in both the steady state and the transient process of a linear time-invariant system with unknown disturbances. The performance of the transient process is illustrated by the concept of overtaking optimality. An overtaking optimal controller with known disturbances is derived to achieve the transient overtaking optimality while guaranteeing steady-state performance. Then, we propose a disturbance independent near-optimal controller, which can achieve optimal steady-state performance and approach the overtaking optimal performance in the transient process. The system performance gap between the overtaking optimal controller and the proposed controller proves to be inversely proportional to the control gains. A case study on a power system with four buses is used to validate the effectiveness of the two controllers. © 2024, CC BY.

关键词： Electromagnetic transients

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Initial-stage performance evolution of solid oxide fuel cells based on polarization analysis 17

Initial-stage performance evolution of solid oxide fuel cell...

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17th International Symposium on Solid Oxide Fuel Cells, SOFC 2021

作者： Wang, Yige Lyu, Zewei Han, Minfang Sun, Zaihong Sun, Kaihua Department of Energy and Power Engineering State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Tsinghua University Beijing100084 China Xuzhou Huatsing Jingkun Energy Co. Ltd. Jiangsu Province Xuzhou221005 China

ISBN: (纸本)9781607685395

The performance evolution of solid oxide fuel cells (SOFCs) is more pronounced and non-linear in the initial stage, determining the output level during subsequent long-term operation. In this study, an industrial-size (10×10 cm2) cell was tested under 0.1 A cm-2 for 96 hours. I-V-P curves and EIS data under different DC bias (0, 0.05, 0.10, 0.30, 0.50, 0.70 A cm-2) were periodically recorded every 24 hours to investigate the mechanism of initialstage performance evolution. The ohmic loss was identified as the main contributor to the total overpotential, especially under large current density. The cell performance increased during 4-24 h due to the enhancement of anode gas-phase diffusion/conversion processes, while the performance degraded significantly during 48- 96 h caused by the deterioration of anode charge transfer reaction. The EIS evolution trend under different DC bias was consistent, while the evolution degree was larger under smaller current density. © 2021 Electrochemical Society Inc.. All rights reserved.

关键词： Deterioration

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Analysis of Fault Characteristics and Distance Protection Adaptability for VSC-HVDC-Connected Offshore Wind Farms

Analysis of Fault Characteristics and Distance Protection Ad...

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IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Fang Peng Houlei Gao Weiying Miao Xinchi Feng Bin Xu Yitong Wu Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Substation Maintenance Center State Grid Hangzhou Power Supply Company Hangzhou China State Grid Nanjing Power Supply Company Nanjing China School of Electrical Engineering Shandong University Jinan China

With the characteristics of low loss, low harmonic content and large transmission capacity, voltage source converter based high voltage direct current transmission (VSC-HVDC) has become the focus of the development for large-capacity and long-distance power transmission system connected with offshore wind farms. However, since the power supplies on both sides are controlled, the fault characteristics are changed, and the performance of the traditional distance protection is influenced. Based on the control strategy, the amplitude and phase angle of the equivalent positive and negative sequence impedances at the two sides of the transmission line are analyzed, and the current phasor expressions of the wind farm side and the VSC-HVDC side of the faulted line are derived. Then the adaptability of distance protection using power frequency component (DPPFC) of transmission line for VSC-HVDC-connected offshore wind farm is analyzed under different fault conditions. The results show that the amplitude and phase angle of the equivalent positive and negative sequence impedances of the wind farm and the VSC-HVDC system are affected by the control strategy of the converter and the fault conditions. The DPPFC is not suitable for VSC-HVDC-connected offshore wind farm system. The ability to avoid the effect of fault resistance of the DPPFC at the wind farm side gets worse. The simulation conducted by EMTP-RV verifies the effectiveness of the analysis.

关键词： Resistance Analytical models power transmission lines power transmission Wind farms Propagation losses power conversion

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In Situ Microplastic Sers Sensor Based on Flexible AU Tapes

SSRN

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SSRN 2024年

作者： Sun, Zhenli Hong, Zijin Zhang, Yiyan Xie, Dan Duan, Fengkui Du, Jingjing MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and Engineering North China Electric Power University Beijing102206 China State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing100085 China University of Chinese Academy of Sciences Beijing China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China

A B S T R A C TMicroplastic analysis is crucial for human health. Thus far, research has primarily focused on investigating microplastics within aqueous environments, while in situ techniques for detecting microplastic particles in the atmosphere remain scarce. Herein, we introduce an innovative flexible sensor for the in-situ detection of microplastics in the atmosphere, using surface-enhanced Raman scattering (SERS) effects. Our sensor, composed of Au nanoparticle (AuNP) tapes fabricated via a novel "drop-coating and peel-off" method, demonstrates outstanding SERS performance. The size, morphology, and electromagnetic field enhancement of the AuNP tape were thoroughly characterized using multiple complementary techniques, including scanning electron microscopy, transmission electron microscopy, UV–vis spectroscopy, atomic force microscopy, and the finite-difference time-domain method. Owing to its exceptional transparency and sensitivity, the AuNP tape facilitates the reliable identification of multi-component microplastics in the atmospheric environment. This study bridges a critical gap in microplastic research and enhances our understanding of microplastic pollution. © 2024, The Authors. All rights reserved.

关键词： Scanning electron microscopy

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MARS: Multi-Agent Deep Reinforcement Learning for Real-Time Workflow Scheduling in Hybrid Clouds with Privacy Protection

MARS: Multi-Agent Deep Reinforcement Learning for Real-Time ...

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International Conference on Parallel and Distributed systems (ICPADS)

作者： Long Cheng Haoyang He Yan Gu Qingzhi Liu Zhiming Zhao Fang Fang State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing China Information Technology Group Wageningen University and Research Netherlands Research Group of Multi-Scale Networked Systems University of Amsterdam Netherlands

ISBN: (数字)9798331515966

ISBN: (纸本)9798331515973

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of $53.18 \%$ and costs by $61.98 \%$ compared to basic techniques, and achieving $20.26 \%$ and $25.71 \%$ improvements over the latest advanced methods, respectively.

关键词： Training Cloud computing Privacy Costs Scalability Deep reinforcement learning Dynamic scheduling Real-time systems Complexity theory Protection

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